Biology subjects

Nan, L.

Publications and source records attributed to Nan, L..

7 recordsLinked to original sources

bioRxiv2025

A Syngeneic Immunocompetent Mouse Model of Gallbladder Cancer Reveals Tumorigenesis and Therapeutic Response

PurposeGallbladder cancer (GBC) is a rare but highly lethal malignancy with one of the poorest prognoses among cancers of the digestive system cancers. However, current experimental models of GBC face critical limitations, particularly their dependence on immunodeficient hosts, which precludes the investigation of the tumor microenvironment. We aimed to establish a novel syngeneic immunocompetent mouse model that recapitulates human GBC and enables the investigation of tumor-immune interactions. Experimental DesignWe engineered a murine cell line (mGBC1-ZH) from normal mouse gallbladder organoids expressing Kras and Trp53 (encoding mouse p53) mutations. Tumorigenic potential of mGBC1-ZH was evaluated by subcutaneous and orthotopic implantation. RNA-Seq and WES was used to demonstrate its characterization and similarity with human GBC. Immunohistochemistry, CCK8, and transwell assays wereused to investigate the role of CXCL5 in GBC. Therapeutic responses to standard first-line chemotherapeutic agents was evaluated in the syngeneic GBC model. ResultsThis model supports both subcutaneous and orthotopic tumor growth in immunocompetent C57BL/6J hosts while preserving hallmark features of human GBC, including biliary epithelial differentiation (CK7+/CK19+), aggressive histopathology, and an immunosuppressive "cold" tumor microenvironment. Genomic characterization revealed recurrent chromosomal instability and copy number alterations mirroring human GBC. Comprehensive transcriptomic profiling revealed profound gene expression changes during the model development, and resembled transcriptional features between mGBC1-ZH and human GBC cell lines and samples. CXCL5 was found to be upregulated in human GBC, and promote proliferation, metastasis, and neutrophils infiltration of GBC in the syngeneic mouse model. Functional validation of the syngeneic GBC model demonstrated therapeutic responsiveness to frontline chemotherapeutics gemcitabine and cisplatin with significant in vivo tumor regression. ConclusionsIn summary, we establised a novel syngeneic GBC mouse model, overcoming the limitations of traditional models by enabling studies in immunocompetent hosts. This model provides valuable insights into the molecular evolution from normal gallbladder cells to transformed cancer cells and establishes a robust platform for both mechanistic studies and therapeutic development.

cancer biology↗

bioRxiv2025

Dissecting a biological electron transport network with electrochemistry

Photosynthetic membranes contain complex networks of redox proteins and molecules which direct electrons along various energy-to-chemical interconversion reactions important for sustaining life on Earth. Analysing and disentangling the mechanisms, regulation and interdependencies of these electron transfer pathways is extremely difficult, owing to the large number of interacting components in the native membrane environment. Whilst electrochemistry is well established for studying electron transfer in purified proteins, it has proven difficult to directly wire into proteins within their native membrane environments, and even harder to probe on a systems-level the electron transfer networks they are entangled within. Here, we show how photosynthetic membranes from cyanobacteria can be directly wired to electrodes to access their complex electron transfer networks. Measurements of native membranes with structured electrodes revealed distinctive electrochemical signatures, enabling analysis from the scale of individual proteins to entire biochemical pathways, as well as their interplay. This includes measurements of overlapping photosynthetic and respiratory pathways, the redox activities of membrane-bound quinones, along with validation using in operando spectroscopic measurements. Importantly, we further demonstrated direct extraction of electrons from native membrane-bound Photosystem I at -600 mV, which is [~]1 V more negative than from purified photosystems. This finding opens up opportunities for biotechnologies for solar electricity, fuel and chemical generation. We foresee this electrochemical method being adapted to analyze other photosynthetic and non-photosynthetic membranes, as well as aiding the development of new biocatalytic, biohybrid and biomimetic systems.

biochemistry↗

bioRxiv2024

Pan-cistrome analysis of the leaf accessible chromatin regions of 214 maize inbred lines

Characterizing the noncoding regions of the genome, particularly the cis-regulatory elements (CREs) located in accessible chromatin regions (ACRs) in gene promoters, is crucial for understanding how gene expression is regulated and how genotype contributes to phenotypic diversity in plants.In this study, we used ATAC-seq to resequence and map the ACRs of 214 maize inbred lines. We identified 82,174 ACRs and reported that 39.55% of them exhibited significant variation across the population. Next, we used the accessibility of ACRs as a quantitative feature and performed a chromatin associability GWAS (caGWAS), resulting in 27,004 caQTLs. Among them, 2,463 were predicted to disrupt the cis-regulatory elements that TF binds in these ACRs, suggesting that TF binding affects chromatin accessibility. Specifically, we identified two caACRs that regulate the expression of fad7, which encodes a fatty acid desaturase and affects the linolenic acid content.Our findings highlight the dynamic nature of maize ACRs and demonstrate that chromatin accessibility information could be used for GWASs, offering key insights into the genetic and regulatory mechanisms of chromatin accessibility and its impact on complex traits in plants.

genomics↗

bioRxiv2022

A novel method revealing animal evolutionary relationships based on milk Mid-infrared

Mid-infrared spectra (MIRS) can effectively reflect the chemical bonds in milk, which has been widely used in dairy herd improvement. However, the relationship between MIRS and animal evolution remains largely unclear. This study firstly found great differences in MIRS and the components of milk by analyzing MIRS information of 12 different mammal species. A five-level discriminant model of evolutionary level based on MIRS was established with a test set kappa coefficient >0.97. In addition, a regression model of genetic distance was also established to estimate the genetic distance of different animal species with a correlation coefficient of R >0.94. These results showed that this method could be used for accurate mammalian evolutionary relationship assessment. We further clarified the potential relationship between MIRS and genes, such as PPP3CA and SCD that could change MIRS by regulating specific milk components. In conclusion, we expand the application of MIRS in animal species identification and evolution research and provide new perspectives for the research on the formation mechanism of different animal milk special components.

evolutionary biology↗

bioRxiv2021

Immunogenicity and efficacy of the COVID-19 candidate vector vaccine MVA SARS 2 S in preclinical vaccination

The severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) has emerged as the infectious agent causing the pandemic coronavirus disease 2019 (COVID-19) with dramatic consequences for global human health and economics. Previously, we reached clinical evaluation with our vector vaccine based on vaccinia virus MVA against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes an infection in humans similar to SARS and COVID-19. Here, we describe the construction and preclinical characterization of a recombinant MVA expressing full-length SARS-CoV-2 spike (S) protein (MVA-SARS-2-S). Genetic stability and growth characteristics of MVA-SARS-2-S, plus its robust synthesis of S antigen, make it a suitable candidate vaccine for industrial scale production. Vaccinated mice produced S antigen-specific CD8+ T cells and serum antibodies binding to S glycoprotein that neutralized SARS-CoV-2. Prime-boost vaccination with MVA-SARS-2-S protected mice sensitized with a human ACE2-expressing adenovirus from SARS-CoV-2 infection. MVA-SARS-2-S is currently being investigated in a phase I clinical trial as aspirant for developing a safe and efficacious vaccine against COVID-19. Significance StatementThe highly attenuated vaccinia virus MVA is licensed as smallpox vaccine, and as vector it is a component of the approved Adenovirus-MVA-based prime-boost vaccine against Ebola virus disease. Here we provide results from testing the COVID-19 candidate vaccine MVA-SARS-2-S, a poxvirus-based vector vaccine that proceeded to clinical evaluation. When administered by intramuscular inoculation, MVA-SARS-2-S expresses and safely delivers the full-length SARS-CoV-2 spike (S) protein, inducing balanced SARS-CoV-2-specific cellular and humoral immunity, and protective efficacy in vaccinated mice. Substantial clinical experience has already been gained with MVA vectors using homologous and heterologous prime-boost applications, including the immunization of children and immunocompromised individuals. Thus, MVA-SARS-2-S represents an important resource for developing further optimized COVID-19 vaccines.

microbiology↗

bioRxiv2019

Autoencoder-based cluster ensembles for single-cell RNA-seq data analysis

BackgroundSingle-cell RNA-sequencing (scRNA-seq) is a transformative technology, allowing global transcriptomes of individual cells to be profiled with high accuracy. An essential task in scRNA-seq data analysis is the identification of cell types from complex samples or tissues profiled in an experiment. To this end, clustering has become a key computational technique for grouping cells based on their transcriptome profiles, enabling subsequent cell type identification from each cluster of cells. Due to the high feature-dimensionality of the transcriptome (i.e. the large number of measured genes in each cell) and because only a small fraction of genes are cell type-specific and therefore informative for generating cell type-specific clusters, clustering directly on the original feature/gene dimension may lead to uninformative clusters and hinder correct cell type identification.\n\nResultsHere, we propose an autoencoder-based cluster ensemble framework in which we first take random subspace projections from the data, then compress each random projection to a low-dimensional space using an autoencoder artificial neural network, and finally apply ensemble clustering across all encoded datasets for generating clusters of cells. We employ four evaluation metrics to benchmark clustering performance and our experiments demonstrate that the proposed autoencoder-based cluster ensemble can lead to substantially improved cell type-specific clusters when applied with both the standard k-means clustering algorithm and a state-of-the-art kernel-based clustering algorithm (SIMLR) designed specifically for scRNA-seq data. Compared to directly using these clustering algorithms on the original datasets, the performance improvement in some cases is up to 100%, depending on the evaluation metrics used.\n\nConclusionsOur results suggest that the proposed framework can facilitate more accurate cell type identification as well as other downstream analyses. The code for creating the proposed autoencoder-based cluster ensemble framework is freely available from https://github.com/gedcom/autoencoder_cluster_ensemble

bioinformatics↗

bioRxiv2017

Parsing Of Compositions And Microstructure Characteristics For Rust-Spots Of Pear Pericarp

The commercial value of Kurles pears pericarp, a popular and favored fruit for its unique aroma and refreshingly crisp texture, had sharply decreased because of a rust breakout of the beloved pear in China during the atmosphere-controlled storage. High performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS) were used to analyze rust spots on the pericarp of Kurle pears. Therefore, the chemical compounds of four various eluates, originating from the rust-colored substance collected from the pears pericarp effected, were identified successfully for the first time, which were just rhein, aloe-emodin, chrysophanol and emodin, respectively. Taken together with microstructure characteristics for rust-spots of Kurle pear pericarp, it was no doubt that these eluates were the main factors affecting the rust spots on the pericarp of the Kurle pears during the atmosphere-controlled storage, which was a sign and consequence resisting the undesirable stress of the external environment.

plant biology↗